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Claude Opus 4.8 vs Llama 3.3 70B Instruct

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.8 and Llama 3.3 70B Instruct.

Anthropic

Claude Opus 4.8

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...

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Meta

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

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Technical Specifications

SpecificationClaude Opus 4.8Llama 3.3 70B Instruct
ProviderAnthropicMeta
Context Window1,000,000 tokens131,072 tokens
Agent Suitability97/10083/100
Time to First Token (TTFT)520 ms280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2026-05-272024-12-06

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.8

$5.00

Llama 3.3 70B Instruct

$0.10

Output Price per Million Tokens

Claude Opus 4.8

$25.00

Llama 3.3 70B Instruct

$0.32

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9540.0%vs8620.0%
Claude Opus 4.8
Llama 3.3 70B Instruct
HumanEvalPython coding & logic synthesis
9720.0%vs8800.0%
Claude Opus 4.8
Llama 3.3 70B Instruct
MATHComplex mathematical problem solving
9410.0%vs7500.0%
Claude Opus 4.8
Llama 3.3 70B Instruct
GPQAGraduate-level expert reasoning
8650.0%vs5200.0%
Claude Opus 4.8
Llama 3.3 70B Instruct
HellaSwagCommonsense reasoning and inference
9920.0%vs8850.0%
Claude Opus 4.8
Llama 3.3 70B Instruct
MT-BenchMulti-turn conversation flow quality
980.0%vs880.0%
Claude Opus 4.8
Llama 3.3 70B Instruct

Claude Opus 4.8 Quirks & Gotchas

  • โ–ธBest-in-class for autonomous code repair and multi-agent orchestration
  • โ–ธPreview model โ€” API may introduce breaking changes without notice

Llama 3.3 70B Instruct Quirks & Gotchas

  • โ–ธStable, well-documented self-hosted option with strong community support
  • โ–ธOutperformed by Llama 4 Maverick for agentic tool-calling workflows